Analysis of experimental design with multivariate response: A contribution using multiblock techniques
| Autor: | Mohamed Hanafi, Gérard Mazerolles, Serge Rudaz, Julien Boccard |
|---|---|
| Přispěvatelé: | Sciences Pour l'Oenologie (SPO), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université Montpellier 1 (UM1)-Université de Montpellier (UM)-Institut National de la Recherche Agronomique (INRA), School of Pharmaceutical Sciences, University of Geneva [Switzerland], Ecole Nationale Vétérinaire, Agroalimentaire et de l'alimentation Nantes-Atlantique (ONIRIS), Université de Genève (UNIGE) |
| Rok vydání: | 2011 |
| Předmět: |
Multivariate statistics
Computer science [SDV]Life Sciences [q-bio] computer.software_genre 01 natural sciences Analytical Chemistry 03 medical and health sciences Matrix (mathematics) Component analysis Application areas [SDV.IDA]Life Sciences [q-bio]/Food engineering Co-inertia Analysis [SPI.GPROC]Engineering Sciences [physics]/Chemical and Process Engineering Spectroscopy 030304 developmental biology 0303 health sciences ANOVA Process Chemistry and Technology 010401 analytical chemistry ASCA Experimental design 0104 chemical sciences Computer Science Applications Data set Data mining Multiblock technique Multiple Algorithm computer Software |
| Zdroj: | Chemometrics and Intelligent Laboratory Systems Chemometrics and Intelligent Laboratory Systems, Elsevier, 2011, 106 (1), pp.65-72. ⟨10.1016/j.chemolab.2010.09.001⟩ |
| ISSN: | 0169-7439 |
| Popis: | Chemometrics Intell. Lab. Syst. ISI Document Delivery No.: 743PB Times Cited: 4 Cited Reference Count: 20 Mazerolles, G. Boccard, J. Hanafi, M. Rudaz, S. Elsevier science bv Amsterdam Si; International audience; In many application areas, experimental approaches both involve an experimental design that determines changes in the studying factors and an untargeted analytical method (IR. LC-MS, NMR,...) used to characterize the samples by a large number of variables. This leads to a resulting data set which can be structured in blocks with respect to the different levels of the experimental factors. Among the methods that have been developed to address this situation, the ANOVA-Simultaneous Component Analysis (ASCA) is the only one which proposes the use of a multiblock technique to date. Nevertheless, other possibilities are achievable. Therefore in this article, we propose 1) to adopt another way of defining and organizing the blocks from the initial matrix and 2) to apply Multiple Co-inertia Analysis (MCoA) a multiblock method different from Simultaneous Component Analysis to manage this new scenario. The complementarities of our proposal with ASCA are demonstrated on a case study related to cheese processing. (C) 2010 Elsevier B.V. All rights reserved. |
| Databáze: | OpenAIRE |
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